Joint Track Machine Learning: An Autonomous Method of Measuring Total Knee Arthroplasty Kinematics From Single-Plane X-Ray Images.

Background: Dynamic radiographic measurements of 3-dimensional (3-D) total knee arthroplasty (TKA) kinematics have provided important information for implant design and surgical technique for over 30 years. However, current methods of measuring TKA kinematics are too cumbersome, inaccurate, or time-consuming for practical clinical application. Even state-of-the-art techniques require human-supervision to obtain clinically reliable kinematics.

Quantification of equine stifle passive kinematics.

Objective: This study aims to quantitatively characterize the passive kinematics of the healthy, soft tissue-intact equine stifle to establish an objective foundation for providing insights into the etiology of stifle disorders and developing a possible surgical treatment for stifle degenerative disease.

Animals: 5 whole-horse specimens.

Procedures: Reflective markers with intracortical bone pins and a motion capture system were used to investigate the stifle joint kinematics.

Posterior cruciate-retaining total knee arthroplasty exhibits small kinematic changes in the first postoperative year.

Purpose: Fluoroscopic knee kinematics have historically been quantified at least 1 year after total knee arthroplasty (TKA). The purpose of this study was to longitudinally assess knee kinematics at 6-12 weeks, 6 months, and 1 year after TKA to determine if earlier evaluation may be justified.

Methods: Twenty-one patients participated after undergoing TKA with a posterior cruciate ligament-retaining fixed-bearing prosthesis.